Informatics and Applications
2017, Volume 11, Issue 2, pp 33-41
CLASSIFICATION BY CONTINUOUS-TIME OBSERVATIONS IN MULTIPLICATIVE NOISE II: NUMERICAL ALGORITHM
Abstract
This is the second part of the paper "Classification by continuous-time observations in multiplicative noise I: Formulae for Bayesian estimate" published in "Informatics and Applications," 2017, 11(1). Investigations are aimed at estimation of a finite-state random vector given continuous-time noised observations. The key feature is that the observation noise intensity is a function of the estimated vector, which makes useless the known results in the optimal filtering. In the first part of the paper, the required estimate is obtained both in the explicit integral form and as a solution to a stochastic differential system with some jump processes in the right-hand side. The second part contains a numerical algorithm of the estimate approximate calculation together with its accuracy analysis. An example illustrating the performance of the proposed estimate is also presented.
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[+] About this article
Title
CLASSIFICATION BY CONTINUOUS-TIME OBSERVATIONS IN MULTIPLICATIVE NOISE II: NUMERICAL ALGORITHM
Journal
Informatics and Applications
2017, Volume 11, Issue 2, pp 33-41
Cover Date
2017-06-30
DOI
10.14357/19922264170204
Print ISSN
1992-2264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
optimal filtering; identifiability; recursive scheme; approximation order; time discretization
Authors
A. V. Borisov 
Author Affiliations
Institute of Informatics Problems, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
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